1. Field of the Invention
The present invention relates to an inspection method, an inspection apparatus, and a facility diagnosis unit.
2. Description of the Related Art
There is an inspection apparatus that takes in a sound or a vibration from an inspection object and inspects if the object is normal or abnormal. The inspection apparatus is used for product inspection and facility diagnosis. According to the facility diagnosis, it is inspected if a working machine and a productive facility operate normally and if it is about time that maintenance such as care and adjustment is necessary on the basis of the vibration and the sound generated by the working machine and the productive facility itself. Specifically, as the facility diagnosis unit, there are an NC finishing machine, a semiconductor plant, and a food plant or the like. According to the product inspection, it is inspected if the product is a normal one or a defective good on the basis of the vibration and the sound generated by the product. It is common to both of them that the inspection is made on the basis of the vibration and the sound. At first, the product inspection will be mainly explained. Some products to be manufactured by the productive facility and a productive system may incorporate a sound source and a vibration source in their insides. In addition, some products may generate a sound or a vibration by their operations. For example, a part such as a motor is incorporated in an electric household appliance such as a refrigerator, an air conditioner, and a washing machine, and if the electric household appliance is driven, it may generate the sound and the vibration in accordance with the rotation of the motor. For example, in an automobile, there are the sound sources or the vibration sources in many parts such as an engine, a power steering, a power sheet, a transmission, and other places.
Some of the sounds and the vibrations of such products may be naturally generated due to the normal operation and other of them may be generated due to the defective operation. The abnormal sound and the abnormal vibration due to the defective operation are caused by abnormal contact in the motor, abnormality of a bearing at a rolling mechanism part, abnormal contact in the rolling mechanism, unbalance of the rolling mechanism, and interfusion of a foreign material or the like. More specifically, there is an abnormal sound such that a rolling part and a fixed part in the motor are rubbed with each other during the rotation only for a moment as an example of the abnormal sound generated by the operation of the mechanism. Some abnormal sounds in the rolling mechanism may be generated due to lack of a gear occurred with frequency once per rotation of a rolling gear, engagement of the foreign material into the gear, and a spot scratch of the bearing or the like. In addition, a sound that a person feels unpleasant may include a sound like “Ki” that is mixed in a prescribed operational sound only for a moment. If only a prescribed operational sound is audible in the normal good, it is possible to regard the product causing the sound like “Ki” as a defective good.
In addition, a pottery product and the product composed of a combination of resin products have no part as the sound source and the vibration sound in itself, however, there is a case that they are inspected if they have a crack or the like. According to the inspection of these products, they are inspected by a sound occurred by hitting the pottery and the resin of the inspection object with a machine tool such as a hammer or the like. If there is no crack in the object, a high tone is generated, and if there is a crack therein, a low tone is generated, so that the inspection can be carried out by this difference in the tone.
In the meantime, “a sound” in the specification may include a sound and a vibration. In the specification, an abnormal sound and an abnormal vibration are generically named as “an abnormal sound” or “an abnormal noise”. In addition, in the specification, “a vibration” is used in the meaning of the vibration and the sound.
It is feared that the sound due to the abnormality and the defect not only may make a person to feel unpleasant but also may occur a failure in the product itself. The good products should be separated from the products causing such sounds by inspecting them in a production process. Therefore, in a production plant, “an organoleptic test” depending on five senses such as an acoustic sense and a sense of touch or the like is normally carried out by an examiner so as to determine if there is an abnormal sound. Specifically, the examiner checks the vibration by hearing a sound by his or her ears and touching the product by his or her hands. In the meantime, the organoleptic test is defined by Z8144 of an organoleptic test terminology JIS (Japanese Industrial Standards).
In the meantime, the organoleptic test depending on the five senses of the examiner requires a skilled examiner and further, the determination result may vary widely depending on individual differences. Moreover, this involves a problem such that it is difficult to have data and numeric values of the determination result of the organoleptic test and its management is also difficult. Therefore, in order to solve such a problem, an abnormal noise inspection apparatus aimed at an inspection based on a quantitative and clear standard is presented. This abnormal noise inspection apparatus is designed to automate an “organoleptic test” step and according to this abnormal noise inspection apparatus, the vibration and the sound of a product driving part is measured by a sensor and an analog signal taken into by the sensor is analyzed and inspected (patent documents JP-A-11-173956, JP-A-11-173909, and JP-A-01-91414). As an analytical method of an analog signal waveform taken into by the sensor, there is a method to apply a band pass filter other than an FFT algorithm.
When inspecting the product by device of such an abnormal noise inspection apparatus, it is necessary that the skilled examiner compares the sample data of the waveform data of the normal product with the sample data of the waveform data of the defective product in advance to find a different between them. Then, the examiner sets and inputs an inspection condition (a model rule and a parameter) so that the abnormal noise inspection apparatus may determine and process the difference between the normal product and the defective product.
The technologies disclosed in these patent documents JP-A-11-173956 to JP-A-01-91414 will be briefly explained below. The technologies relate to a frequency analytical apparatus applying an FFT algorithm and it abstracts a time region component of the taken vibration waveform from a frequency region by device of a fast Fourier transformation algorithm. Obtaining an amount of characteristic of the corresponding component on the basis of an abnormal characteristic that is found from among the extracted frequency components, the abnormality is determined on the basis of the amount of characteristic and the determination result of the abnormality is outputted.
It is a matter of course that the extracted amount of characteristic is not limited to the frequency component. There is an effective value of the waveform data on the basis of the vibration and the sound generated from the inspection object, the maximum vibration level, and the number of climaxes and others various kinds of things. In accordance with enlargement of the kinds of the inspection object, the kind of the amount of characteristic is also increased.
A conventional inspection apparatus extracts the amount of characteristic from among the waveform data on the basis of the vibration and the sound that are generated from the inspection object so as to determine whether or not the inspection object complies with a model rule that has been prepared in advance, and the model rule is only based on the defective product such as the frequency component corresponding to the above-described generation region of the abnormal vibration and the abnormal sound. Then, when the object does not correspond to the defective product, the apparatus determines that the product is a normal product.
In other words, in order to design such an inspection apparatus, at first, a plurality of the sample data of the defective products and the sample data of the normal products of the inspection object are prepared, and comparing both, a difference of the characteristic is found. The amount of characteristic that is suitable for only extracting the defective product as compared to a vibration characteristic of the normal product or a sound characteristic thereof is found on the basis of the sample data of the defective product, and a model rule for determining the discrimination between the normal product and the defective product is made and registered. This model rule is a determination algorithm for determining the normal product and the defective product and it is a common rule that can be applied to any of the plural sample data. Conventionally, there are various methods with related to how to find the amount of characteristic suitable for determination, how to extract the amount of characteristic effectively, and how to find a determination algorithm. In any case, it is an essential condition to decide a model rule on the basis of the sample data of the defective product and this is a defined fact and a stereotype.
In the case that the sample data of the defective product cannot be prepared, the model rule cannot be developed, so that this involves a problem such that the inspection apparatus cannot be designed. Further, in order to determine what kinds of abnormality, it is necessary to prepare the sample data for each kind of defect, however, sometimes the sample cannot be obtained well at an initial status upon starting a productive line. In addition, according to such an inspection of the defective product or the apparatus to inspect the kinds of the defect, only the defective product of which sample data is prepared and of which model rule has been made can be determined and it is difficult to detect an unknown defective product.
On the other hand, a determination of good or bad on the basis of the sample data of the defective product as a conventional case is suitable for a productive facility and a productive line that are shifted to a mass production system that the kinds of defect and abnormality are specified to some extent, however, upon start of the productive line, the kinds of defect cannot be specified, unknown kinds of defects appear consequently, and it is not determined that plural kinds of defect are combined, so that it is difficult to collect the sample data and the model rule, and this makes it impossible to effectively apply the inspection apparatus.
Even if the sample data of the defective product can be prepared well and the inspection apparatus can be designed, with respect to some kind of defective product, finding out a cause of generation of the defective product day by day, the productive facility and the productive line are improved so as to prevent the defective product from being generated. Therefore, this is very ineffective since the sample data are collected and the model rule is made with respect to the defective product that is not generated at pains. In addition, it takes a large amount of labor and time because it is necessary that the sample data of the defective product are collected whenever a new kind of defective product appears and an effective model rule is made on the basis of these sample data. Therefore, this involves a problem such that, when the new kind of defective product appears, the inspection apparatus cannot determine this new kind of defective product. Thus, this involves a problem such that the inspection apparatus cannot be applied effectively due to an unclear defective product such as the defective product to be eradicated and a newly generated kind of defective product or the like.
In the meantime, the facility diagnosis has the same problem. Also in the facility diagnosis, in order to diagnose the defect, it is necessary to collect a plurality of sample data of the defect and to make a model rule, and in order to diagnose the kind of defect, it is necessary to collect a plurality of sample data for each kind of the defect and to make a model rule for each kind of the defect. However, there is a transit period in the facility diagnosis, so that it is not determined that the diagnosis object becomes defective (not becomes normal) when what vibration and what sound are generated by a working machine of the diagnosis object and the productive facility itself and it is not determined that what kind of defect is generated when what kind of vibration and sound are generated at an initial status and they are not clear. It is a matter of course that a new kind of defect is generated. In other words, also in the facility diagnosis, as same as the product inspection, there are unclear defects.